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PNG Image - 1.4 MB -
MD5: daed40d112b503f118b5565b7451b475
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PNG Image - 1.5 MB -
MD5: eb1dd15a28028ad3fd7fbb3b26066806
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Tabular Data - 1.0 KB - 12 Variables, 17 Observations - UNF:6:Zzy1jgtSupc2h1VgeNS9zg==
A planilha inclui informações referentes aos materiais utilizados, ensaios realizados, e pastas produzidas no estudo. |
MS Excel Spreadsheet - 153.6 KB -
MD5: 5cb9995deff6277a1bb8d71be87e1597
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ZIP Archive - 417.2 KB -
MD5: 870c5dd5f46130ca1e95a590fed06752
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Markdown Text - 3.4 KB -
MD5: 9a6eede339a2ac0d6665b0f784149221
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R Syntax - 39.7 KB -
MD5: ba9f43aab8cce1309d079e7387c7fae8
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MS Excel Spreadsheet - 57.3 KB -
MD5: ae5b2d4d873c6b374831aa0629ff348e
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Mar 3, 2026 -
Exemplary classes generated for the study of generalized resource allocation with priorities
MS Word - 312.7 KB -
MD5: 85f26b04cee343565c3f89a6cf9620e7
Five instances were created by varying the number of resources of type m, aiming to evaluate the impact of machine (or physical resource) availability on the performance of the proposed model. |
Mar 3, 2026 -
Exemplary classes generated for the study of generalized resource allocation with priorities
MS Word - 251.4 KB -
MD5: 90ceae4f78b163561c2c1c0e2393e22b
Five instances were developed by changing the number of items to be produced. This class allows the analysis of how workload variations influence allocation and planning decisions. |
